天津市河流生态完整性评价

对河流生态健康状况进行评价,可为河流治理和生态修复提供依据.基于2018年8—9月天津市河流现场调查获取的物理、化学和生物群落指标（浮游动物、浮游植物、底栖动物、鱼类、水生大型植物、陆生植物）数据,构建包含物理完整性、化学完整性和生物完整性在内的河流IEI（index of ecological integrity,生态完整性指数）评价体系,对天津市河流生态健康状况进行评价.根据生物栖息地评分和水质状况确定参照点位,采用标准化方法筛选候选指标,应用层次分析法计算三部分指标权重,最终得出天津市河流生态健康评价结果.结果表明:①IEI评价结果显示,天津市河流生态健康状况等级为“健康”的样点占18.8%,“较好”的样点占28.1%,“一般”的样点占40.6%,“较差”的样点占6.3%,“差”的样点占6.3%,天津市河流生态健康状况整体处于“一般”水平.②相关性分析表明,ρ（NH₄+-N）和ρ（COD_Mn）超标是造成天津市水质达不到功能区标准的主要原因,同时也是影响河流生态健康的主要因素.研究显示,IEI评价法能够较为敏感地响应研究区面临的环境压力,适用于评价研究区河流生态健康.      

深圳市综合水质指数研究及其在水资源资产评估上的应用

自然资源资产评估技术是开展自然资源资产负债表实践和实行环境责任离任审计的重要技术支撑。水资源作为一项重要自然资源,如何有效评估水资源资产是不可回避的问题。论文以深圳市为研究区域,一是采用综合污染指数法和主成分分析法,以总氮、氨氮、总磷、化学需氧量、生化需氧量、固体悬浮物为指标参数构建了深圳市综合水质指数以评价水资源综合水质。二是以该综合水质评估模型为基础,通过采用治污成本法分析综合水质与治污成本间的关系,从而构建深圳市景观水和饮用水资源的价值量评估模型。论文还以深圳市大鹏新区为试点开展了水资源价值量评估,评估结果显示,2015年大鹏新区景观水和饮用水资源的价值量分别为3.60亿、0.35亿元。     

马莲河流域河水化学特征和化学风化过程分析

采用Gibbs图解和端元分析方法研究了马莲河水化学特征、离子来源和化学风化作用,利用质量平衡正演模型评价了各风化作用对水化学组分的贡献率。结果表明,马莲河水为高TDS咸水,阳离子以Na~+、Mg~(2+)为主,阴离子以Cl~-、SO_4~(2-)为主;沿河水流向TDS降低,水化学类型由Cl-Na型演变为HCO_3·SO_4-Na·Mg型;河水化学组分的主要形成作用为化学风化,蒸发盐主导了流域风化过程,对离子组分平均贡献率高达76.5%,硅酸盐和碳酸盐风化较弱;化学风化具空间变异,从上游到下游,硫酸盐和碳酸盐贡献率增加,岩盐贡献率降低。岩性是控制流域化学风化作用的首要因素,降雨量和径流量可能也有一定影响。     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Determination of organophosphorus pesticides and related compounds in water samples by membrane extraction and gas chromatography

A membrane extraction-gas chromatography method was developed fordetermination of organophosphorus pesticides and related compounds including methamidophos, DDVP, dimethoate, methyl parathion, parathion, thiophosphoric acid trimethyl ester, and thiophosphoramidic acid dimethyl ester in water samples. In thismethod, surface-modified acetic cellulose membranes were used to extract the target analytes in water samples, the extracted analytes were back-extracted into a small amount of methanol, andgas chromatography with pulsed flame photometric detector (GC-PFPD) was used to determine the concentrations of targetanalytes in the extracts. The recoveries obtained for thetarget analytes spiked into the water samples ranged from 66to 94%. The method detection limit for each target analyte was 0.05 g L^-1. The method developed in this study had shown the advantages of being cheap, simple, fast, and reliable. It had been used successfully to determine the concentrations of target analytes in river water samples.     

长江流域等重污染行业经济和污染贡献率剖析

应用"污染贡献率"这一指标,分析了长江、黄河、珠江和松花江流域COD和氨氮排放的重污染行业以及地区分布,指出了各流域COD和氨氮排放的控制重点.同时分析了各流域重污染行业的经济贡献率,最后结合行业的污染贡献率和经济贡献率以及行业在地区所占的比例,提出了几点重要的结论.     

汉江水质评价的化学计量学研究

运用因子分析法对汉江各主要水质断面进行水质因子分析及综合评价,通过各主因子的方差贡献及因子得分得出各水质因子的赋权值,从而对所取断面进行水质污染程度的综合评价、分析与排序。同时运用聚类分析法对汉江17个断面的水质污染相似性进行分析,给出分类处理结果。     

平顶山市湛河水污染现状及防治对策

以“九五”期间平顶山市湛河水质例行监测结果为依据，分析了湛河水污染现状、特征及原因，并提出综合性湛河污染防治对策。     

Macroinvertebrate Regionalisation for use in the Management of Aquatic Ecosystems in Victoria, Australia

The development of a broader, more holistic approach to aquaticecosystem management has been called for in recent years. Physical and chemical objectives alone are no longer consideredsufficient for the protection of aquatic ecosystems and shouldbe supplemented with biological objectives. The ubiquitousand sedentary nature of macroinvertebrates, combined with theirmeasurable response to environmental conditions, favour their use as important indicators in environmental policies. To establish biological objectives, there is a need for a regionalframework to limit the variability between ecosystems. Past studies have demonstrated that an a posteriori regionalisationapproach may be more useful than an a priori approach in explaining single component (e.g. macroinvertebrates) patternsacross ecosystems. This is particularly important as aquaticresource management agencies often focus on one or twocomponents of the ecosystem to assess environmental health. This study uses an a posteriori method to delineate and describebiological regions based on edge and riffle macroinvertebrate data. The regionalisation will provide a framework for settingbiological objectives, based on the range of reference conditionsmeasured within each separate region. The objectives will includeregional checklists for taxa and biotic indices. Predictive modelling in the style of RIVPACS or AUSRIVAS will also be usedwithin each region to develop objectives, incorporating local, regional and systematic features as predictor variables.     

跨界河流的水质监测(1)

水质监测是任何水资源管理必不可少的组成部分,水质监测与评价不仅可对水污染问题进行鉴别和评估,而且可以验证污染控制措施是否正确以及污染源是否遵守了相关的环保法规、制度、文章讨论了综合监测系统的对策、网络设计、采样与分析、数据处理与报告,还讨论了必需的科学的组织形式。以4条跨界河流[欧洲的莱茵河(Rhine)和多瑙河(Danube)、南美的拉普拉塔河(La Plata)、东南亚的湄公河(Mekong)]为例阐述了现代意义的监测方法学。对于工业化程度高的流域(如莱茵河和多瑙河),早期预警系统尤为重要。最后探讨了新的性价比好的污染监测方法以及如何避免产生数据很多,但信息量很少的状况。